Generative AI and Precision Medicine A major breakthrough of this project has been the development of AutoCT, a generative AI-based tool that automates CT registration, segmentation and quantification. This technology not only improves the accuracy of TBI diagnosis but also reduces the workload on neuroradiologists, thereby helping prevent burnout and allowing clinicians to focus on patient care. Kristofer Bouchard, Ph.D., neuroscientist at Lawrence Berkeley National Laboratory and UC Berkeley, has brought his expertise in generative-AI and health to the project.
Stock image: MRI of brain trauma
Bouchard has played a key role in refining these AI algorithms, ensuring they not only enhance diagnostic precision but also provide interpretable results that clinicians can trust. “A critical first step towards personalized TBI treatments is increasing the precision with which we describe brain injury features” he said, “and then predicting outcomes based on multimodal data, including imaging, blood biomarkers and medical history.”
THIS TECHNOLOGY NOT ONLY IMPROVES THE ACCURACY OF TBI DIAGNOSIS BUT ALSO REDUCES THE WORKLOAD ON NEURORADIOLOGISTS, THEREBY HELPING PREVENT BURNOUT AND ALLOWING CLINICIANS TO FOCUS ON PATIENT CARE.
TBI Research Lays Groundwork for Other Diseases Beyond the immediate benefits for TBI care, this project has laid the groundwork for future generative-AI applications in medicine. The tools developed—particularly those for integrating medical imaging with clinical data—could be extended to other complex diseases that rely on combined decision support from imaging and biomarkers. The UC Noyce Initiative’s funding has not only accelerated this research but has also fostered new collaborations and created a lasting platform for ongoing innovation, according to the team. The team has already begun sharing their findings with the broader scientific community. Meanwhile, the project has also nurtured new talent. Research assistants and postdoctoral scholars at UC Berkeley and UCSF have contributed to this initiative, with one research assistant now pursuing graduate studies. “This collaboration has been a massive effort, from coordinating data curation to deploying large-scale AI models,” said Manley. “With the foundation now in place, we are well-positioned to continue streamlining the workflow from raw data to actionable clinical results—an effort that could transform precision medicine for TBI and beyond.” ◆
26 Impact Report 2023 - 24 | UC NI
Made with FlippingBook Annual report maker